A Bayesian inverse-problem framework for deriving uncertainty-aware adaptive algorithms in active noise control

Iman Ardekani, Waleed Abdulla, Jari Kaipio

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DOI: 10.1121/10.0043943
Published: 2026-06-01
Container: The Journal of the Acoustical Society of America
Publisher: Acoustical Society of America (ASA)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1121/10.0043943,
  title = {A Bayesian inverse-problem framework for deriving uncertainty-aware adaptive algorithms in active noise control},
  author = {Iman Ardekani and Waleed Abdulla and Jari Kaipio},
  year = {2026},
  journal = {The Journal of the Acoustical Society of America},
  doi = {10.1121/10.0043943},
  url = {https://doi.org/10.1121/10.0043943}
}

RIS

TY  - JOUR
TI  - A Bayesian inverse-problem framework for deriving uncertainty-aware adaptive algorithms in active noise control
AU  - Iman Ardekani
AU  - Waleed Abdulla
AU  - Jari Kaipio
PY  - 2026
JO  - The Journal of the Acoustical Society of America
DO  - 10.1121/10.0043943
UR  - https://doi.org/10.1121/10.0043943
ER  -

APA

Ardekani, I., Abdulla, W., & Kaipio, J. (2026). A Bayesian inverse-problem framework for deriving uncertainty-aware adaptive algorithms in active noise control. The Journal of the Acoustical Society of America. https://doi.org/10.1121/10.0043943

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crossref · retrieved 2026-11-10T07:04:45.976Z